489 20 11858 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Sentiment Analysis of Stress Among the Students Amidst the Covid Pandemic Using Global Tweets Subject The topic of the resource BERT; Deep learning; LSTM; Machine learning; Sentiment analysis; SVM; Twitter Description An account of the resource Covid-19 pandemic has affected the lives of people across the globe. People belonging to all the sectors of the society have faced a lot of challenges. Strict measures like lockdown and social distancing have been imposed several times by governments throughout the world. Universities had to incorporate the online method of teaching instead of the regular offline classes to implement social distancing. Online classes were beneficial to most of the students; at the same time, there were many difficulties faced by the students due to lack of facilities to attend classes online. Students faced a lot of challenges, and a sense of anxiety was prevalent during the uncertain times of the pandemic. This research article analyzes the stress among students considering the tweets across the globe related to students stress. The algorithms considered for classification of tweets as positive or negative are support vector machine (SVM), bidirectional encoder representation from transformers (BERT), and long short-term memory (LSTM). The accuracy of the abovementioned algorithms is compared. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Jyothsna R.; Rohini V.; Paulose J. Source A related resource from which the described resource is derived Smart Innovation, Systems and Technologies, Vol-317, pp. 317-324. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-19-6068-0_31" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-6068-0_31</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145010365&doi=10.1007%2F978-981-19-6068-0_31&partnerID=40&md5=d53e6ff3872ff78ede9deb4a491cff80" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145010365&doi=10.1007%2f978-981-19-6068-0_31&partnerID=40&md5=d53e6ff3872ff78ede9deb4a491cff80</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 21903018; ISBN: 978-981196067-3 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Jyothsna R., Christ University, Bangalore, India; Rohini V., Christ University, Bangalore, India; Paulose J., Christ University, Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Sentiment Analysis on Amazon Product Review Subject The topic of the resource Machine Learning; Natural Language Processing; Sentiment Analysis Description An account of the resource Users throughout the world may now access massive amounts of data thanks to the internet and social media platforms. [5] In every facet of human existence, electronic commerce (e-commerce) plays a crucial role. E-commerce is a marketing approach that enables businesses and consumers to buy and sell things via the internet. When buyers look for product information and compare alternatives online, they generally have access to dozens or hundreds of product reviews from alternative shoppers. Machine learning is the most appropriate approach to training a neural network in today's age of practical artificial intelligence. So implementing a model to polarize those reviews and learn from them would make passing hundreds of comments a lot easier. [24] The interpretation will be a very basic product with positive, neutral, and negative polarization. The product is checked. This study suggests a sentiment evaluation model for shopper reviews based on the object and emotive word mining for emotional level analysis using machine learning approaches. 2022 IEEE. Creator An entity primarily responsible for making the resource Kamalesh B.; Vijayalakshmi S. Source A related resource from which the described resource is derived Proceedings - 2022 4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022, pp. 846-848. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICAC3N56670.2022.10074287" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICAC3N56670.2022.10074287</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152189839&doi=10.1109%2FICAC3N56670.2022.10074287&partnerID=40&md5=22917ca4d569867b577a4a549f423292" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152189839&doi=10.1109%2fICAC3N56670.2022.10074287&partnerID=40&md5=22917ca4d569867b577a4a549f423292</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166547436-8 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Kamalesh B., Christ (Deemed to Be University), Data Science, Pune, India; Vijayalakshmi S., Christ (Deemed to Be University), Data Science, Pune, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Sentiment Analysis on Banking Feedback and News Data using Synonyms and Antonyms Subject The topic of the resource control distance; datasets; ELECTRA; sentiment analysis; sentiment score; Synonyms and antonyms Description An account of the resource Sentiment analysis is crucial for deciphering customers enthusiasm, frustration, and the market mood within the banking sector. This importance arises from financial datas specialized and sensitive nature, enabling a deeper understanding of customer sentiments. In todays digital and social marketing landscape within the banking and financial sector, sentiment analysis is significant in shaping customer insights, product development, brand reputation management, risk management, customer service improvement, fraud detection, market research, compliance regulations, etc. This paper introduces a novel approach to sentiment analysis in the banking sector, emphasizing integrating diverse text features to enable dynamic analysis. This proposed approach aims to assess the sentiment score of distinct words used within a document and classify them as positive, negative, or neutral. After rephrasing sentences using synonyms and antonyms of unique words, the system calculates sentence similarity using a distance control mechanism. Then, the system updates the dataset with the positive, negative, and neutral labels. Ultimately, the ELECTRA model utilizes the self-trained sentiment-scored data dictionary, and the newly created dataset is processed using the SoftMax activation function in combination with a customized ADAM optimizer. The approachs effectiveness is confirmed through the analysis of post-bank customer feedback and the phrase bank dataset, yielding accuracy scores of 92.15% and 93.47%, respectively. This study stands out due to its unique approach, which centers on evaluating customer satisfaction and market sentiment by utilizing sentiment scores of words and assessing sentence similarities. 2023, Science and Information Organization. All rights reserved. Creator An entity primarily responsible for making the resource Mohanty A.; Cherukuri R.C. Source A related resource from which the described resource is derived International Journal of Advanced Computer Science and Applications, Vol-14, No. 12, pp. 934-944. Publisher An entity responsible for making the resource available Science and Information Organization Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.14569/IJACSA.2023.0141294" target="_blank" rel="noreferrer noopener">https://doi.org/10.14569/IJACSA.2023.0141294</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183092319&doi=10.14569%2FIJACSA.2023.0141294&partnerID=40&md5=dac49980a421a56d37bb8e0345f9965f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183092319&doi=10.14569%2fIJACSA.2023.0141294&partnerID=40&md5=dac49980a421a56d37bb8e0345f9965f</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 2158107X Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mohanty A., Department of Computer Science and Engineering CHRIST (DEEMED TO BE UNIVERSITY), Bangalore, 560074, India; Cherukuri R.C., Department of Computer Science and Engineering CHRIST (DEEMED TO BE UNIVERSITY), Bangalore, 560074, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Sentiment Analysis On Covid-19 Related Social Distancing Across The Globe Using Twitter Data Description An account of the resource Covid 19 pandemic has devastated the lives of several people across the globe. Social distancing is considered a major preventive measure to stop the spread of Covid 19. The practice of social distancing has caused a sense of loneliness and mental health problems in society. The aim of this study is to consider global tweet data with social distancing keywords for analyzing the sentiments behind them. Classification of tweets as positive or negative is carried out using Support Vector Machine and Logistic Regression. The Electrochemical Society Creator An entity primarily responsible for making the resource Jyothsna R.; Rohini V.; Paulose J. Source A related resource from which the described resource is derived ECS Transactions, Vol-107, No. 1, pp. 3995-4001. Publisher An entity responsible for making the resource available Institute of Physics Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1149/10701.3995ecst" target="_blank" rel="noreferrer noopener">https://doi.org/10.1149/10701.3995ecst</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130525098&doi=10.1149%2F10701.3995ecst&partnerID=40&md5=f85432638fe5f928c8ce501afafa9ff3" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130525098&doi=10.1149%2f10701.3995ecst&partnerID=40&md5=f85432638fe5f928c8ce501afafa9ff3</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 19386737; ISBN: 978-160768539-5 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Jyothsna R., Department of Computer Science, Christ University, Karnataka, Bengaluru, India; Rohini V., Department of Computer Science, Christ University, Karnataka, Bengaluru, India; Paulose J., Department of Computer Science, Christ University, Karnataka, Bengaluru, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Sentiment Analysis on Educational Tweets: A Case of National Education Policy 2020 Subject The topic of the resource machine learning; performance metrics; Sentiment analysis; sentiment score Description An account of the resource Due to COVID-19 pandemic lockdowns, the transition from traditional class-room-based approaches, there has been rise in online education. There is a growing need to adopt the best global academic and innovative practices and implement the National Education Policy-2020 (NEP) in Indian education. This study uses a dataset, NEPEduset, created by gathering tweets about education. An attempt has been made in this study to examine the tweets by preprocessing, generating labels or sentiments using standard tools and libraries in Python language, applying and comparing various machine learning (ML) algorithms. ML approaches are powerful and used in various applications ranging from sentiment analysis, text analysis, natural language processing (NLP), image processing, object detection. ML methods are widely used in sentiment analysis tasks and text annotations. This work uses Text-Blob, Valence Aware Dictionary for Sentiment Reasoning (VADER), and a Customized method, SentiNEP to analyze the sentiment score of tweets' text. SentiNEP method is shown is produce better results for various experiments conducted for the dataset, NEPEduset. Various supervised ML models have been applied for text classification of user sentiment. Word2Vec feature extraction technique has been applied to build and evaluate the models. Performance metrics such as precision, accuracy, F1 score and recall have been used to evaluate the ML models. The results reveal that the support vector machine and random forest classifiers achieve higher accuracy with Word2Vec. The performance results have been compared with VADER, TextBlob and SentiNEP. It has been found that the SentiNEP method produces better results. 2023 IEEE. Creator An entity primarily responsible for making the resource Siddique M.M.; Kumar S. Source A related resource from which the described resource is derived Proceedings of IEEE InC4 2023 - 2023 IEEE International Conference on Contemporary Computing and Communications Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/InC457730.2023.10262944" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/InC457730.2023.10262944</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174741364&doi=10.1109%2FInC457730.2023.10262944&partnerID=40&md5=408f17b347bd680b0281c48ad8fc512d" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174741364&doi=10.1109%2fInC457730.2023.10262944&partnerID=40&md5=408f17b347bd680b0281c48ad8fc512d</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835033577-4 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Siddique M.M., CHRIST (Deemed to Be University), Department of Computer Science and Engineering, Kengeri, Bengaluru, India; Kumar S., CHRIST (Deemed to Be University), Department of Computer Science and Engineering, Kengeri, Bengaluru, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Sentiment Analysis on Indian Government Schemes Using Twitter data Subject The topic of the resource Accuracy in graph; Data Cleaning; Data fetching; Machine Learning; Sentiment Analysis; Wordlist Creation Description An account of the resource People use social media for entertainment, fetching information, news, business, communication and many more. Few of such social media applications are Facebook, Twitter, WhatsApp, Snapchat and so on. Twitter is one among the micro blogging websites. We are using Twitter mainly because it has gained a lot of media attention. The text written is referred to as tweets, where a common man can tweet or can write their hearts out. We would be fetching the direct responses from the public and hence the data is more real-time. First step is to fetch the tweets on a particular scheme using python language code followed by the cleaning process then comes the creation of bag of words. Later these bags of words are given as an input to the algorithms. Finally, after training the algorithms, we will be getting the sentiment of the public on that scheme. 2019 IEEE. Creator An entity primarily responsible for making the resource Rekha V.; Raksha R.; Patil P.; Swaras N.; Rajat G.L. Source A related resource from which the described resource is derived 2019 International Conference on Data Science and Communication, IconDSC 2019 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2019-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/IconDSC.2019.8817036" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/IconDSC.2019.8817036</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072765284&doi=10.1109%2FIconDSC.2019.8817036&partnerID=40&md5=1368957f6b979c4e5b62ae1e054706b1" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072765284&doi=10.1109%2fIconDSC.2019.8817036&partnerID=40&md5=1368957f6b979c4e5b62ae1e054706b1</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-153869319-3 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Rekha V., Department of Computer Science and Engineering, Christ, Deemed to be University, Bangalore, India; Raksha R., Department of Computer Science and Engineering, SJBIT, Bangalore, India; Patil P., Department of Computer Science and Engineering, SJBIT, Bangalore, India; Swaras N., Department of Computer Science and Engineering, SJBIT, Bangalore, India; Rajat G.L., Department of Computer Science and Engineering, SJBIT, Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Sentiment Analysis on Live Webscraped YouTube Comments Using VADER Sentiment Analyzer Subject The topic of the resource Dataframes; Google API V3; Lemmatization; Live web scraping; NLP; Pandas; Sentiment analysis; Stemming; Tokenization; VADER Description An account of the resource After the covid disease came in the beginning of 2020s, the amount of people using social medias has increased dramatically. So as an effect of that, the viewers and engagement in one of the worlds largest platform by google called YouTube also increased. So many new content creators also born during these times. So this project is getting the sentiment from the audience or user to the content creators by which they can improve their content quality. This research holds promise in harnessing the power of sentiment analysis to enhance the overall YouTube experience and inform content creators and platform administrators in their decision-making processes. Understanding these trends is vital for content creators, as it can offer invaluable insights into viewer engagement and preferences. By gaining a deeper understanding of how viewers react to content, creators can refine their strategies, tailor their content to their audience, and enhance the overall quality of videos. By incorporating sentiment information into recommendations, the platform can suggest videos that resonate more effectively with users, thereby increasing engagement and satisfaction. The identification of negative sentiment and harmful comments enables YouTubes content moderation systems to proactively address issues such as hate speech, harassment, and toxicity. This, in turn, contributes to a safer and more welcoming space for users to share their thoughts and opinions. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. Creator An entity primarily responsible for making the resource Abhijith S.; Pani A.K. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-1112 LNNS, pp. 115-126. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-97-6684-0_11" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-97-6684-0_11</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215665758&doi=10.1007%2F978-981-97-6684-0_11&partnerID=40&md5=bc94ae2cd74433d04dcc0e20a4a21ce0" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215665758&doi=10.1007%2f978-981-97-6684-0_11&partnerID=40&md5=bc94ae2cd74433d04dcc0e20a4a21ce0</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981976683-3 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Abhijith S., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Bangalore, India; Pani A.K., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Sentiment analysis on social media data using intelligent techniques Subject The topic of the resource Convolutional Neural Networks (CNN); Emotions; Machine Learning; Multi-layer Perceptron (MLP); Sentiment Analysis Description An account of the resource Social media gives a simple method of communication technology for people to share their opinion, attraction and feeling. The aim of the paper is to extract various sentiment behaviour and will be used to make a strategic decision and also aids to categorize sentiment and affections of people as clear, contradictory or neutral. The data was preprocessed with the help of noise removal for removing the noise. The research work applied various techniques. After the noise removal, the popular classification methods were applied to extract the sentiment. The data were classified with the help of Multi-layer Perceptron (MLP), Convolutional Neural Networks (CNN). These two classification results were checked against the others classified such as Support Vector Machine (SVM), Random Forest, Decision tree, Nae Bayes, etc., based on the sentiment classification from twitter data and consumer affairs website. The proposed work found that Multi-layer Perceptron and Convolutional Neural Networks performs better than another Machine Learning Classifier. International Research Publication House. Creator An entity primarily responsible for making the resource Panguila K.F.M.; Chandra J. Source A related resource from which the described resource is derived International Journal of Engineering Research and Technology, Vol-12, No. 3, pp. 440-445. Publisher An entity responsible for making the resource available International Research Publication House Date A point or period of time associated with an event in the lifecycle of the resource 2019-01-01 Identifier An unambiguous reference to the resource within a given context <a href="" target="_blank" rel="noreferrer noopener"></a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064499954&partnerID=40&md5=4f3bcc4336e5300c3c63560976d67b80" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064499954&partnerID=40&md5=4f3bcc4336e5300c3c63560976d67b80</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 9743154 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Panguila K.F.M., Department of Computer Science, CHRIST (Deemed to be University), India; Chandra J., Department of Computer Science, CHRIST (Deemed to be University), India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Sentiment Analysis on Time-Series Data Using Weight Priority Method on Deep Learning Subject The topic of the resource Deep learning; Natural Language Processing; Polarity Identification; Sentiment Analysis; Time-series data; Weight priority Description An account of the resource Sentiment Analysis (SA)is the process to gain an overview of the public opinion on certain topics and it is useful in commerce and social media. The preference on certain topics can be varied on different time periods. To analyze the sentiments on topics in different time periods, priority weight based deep learning approaches like Convolutional-Long Short-Term Memory (C-LSTM)and Stacked- Long Short-Term Memory (S-LSTM)is explored and analyzed in this research. The research method focuses on three phases. In the first phase text data (review given by the customers on various products)is collected from social networking e-commerce site and temporal ordering is done. In the second phase, different deep learning models are created and trained with different time-series data. In the final phase the weights are assigned based on temporal aspect of the data collected. For the obtained results verification and validation processes are carried out. Precision and recall measures are computed. Results obtained shows better performance in terms of classification accuracy and F1-score. 2019 IEEE. Creator An entity primarily responsible for making the resource Yeo I.; Balachandran K. Source A related resource from which the described resource is derived 2019 International Conference on Data Science and Communication, IconDSC 2019 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2019-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/IconDSC.2019.8816985" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/IconDSC.2019.8816985</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072777448&doi=10.1109%2FIconDSC.2019.8816985&partnerID=40&md5=4c9dac6c2f8bbd8d53eb2dbfe9cc3b9c" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072777448&doi=10.1109%2fIconDSC.2019.8816985&partnerID=40&md5=4c9dac6c2f8bbd8d53eb2dbfe9cc3b9c</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-153869319-3 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Yeo I., Dept. of Computer Science and Engineering, CHRIST, Deemed to be University, Bangalore, India; Balachandran K., Dept. of Computer Science and Engineering, CHRIST, Deemed to be University, Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Sentiment analysis with NLP: A catalyst for sales in analyzing the impact of social media ads and psychological factors online Description An account of the resource This chapter explores the role of sentiment analysis, powered by NLP, in boosting sales amidst "Intersection of AI and Business Intelligence in Data-Driven DecisionMaking." It analyzes how social media ads and psychological factors shape online shopping behavior, demonstrating how sentiment analysis drives digital commerce sales. Sentiments from platforms like Twitter, Facebook, and Instagram are categorized into positive, negative, or neutral using advanced NLP algorithms. The chapter delves into psychological factors such as trust, credibility, brand perception, and emotional responses triggered by social media ads. Through sentiment analysis, patterns and correlations between sentiment expressions and consumer actions are revealed, illuminating the impact of social media advertising on online shopping behavior. This insight aids marketers in optimizing digital strategies, developing effective campaigns to enhance sales performance, and engaging customers in the online shopping domain. 2024, IGI Global. All rights reserved. Creator An entity primarily responsible for making the resource Jose J.M.; Narayanan P. Source A related resource from which the described resource is derived Intersection of AI and Business Intelligence in Data-Driven Decision-Making, pp. 211-256. Publisher An entity responsible for making the resource available IGI Global Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3693-5288-5.ch008" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3693-5288-5.ch008</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215356394&doi=10.4018%2F979-8-3693-5288-5.ch008&partnerID=40&md5=de39af53e23c3986732652bf680cd304" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215356394&doi=10.4018%2f979-8-3693-5288-5.ch008&partnerID=40&md5=de39af53e23c3986732652bf680cd304</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-836935289-2; 979-836935288-5 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Jose J.M., Christ University, India; Narayanan P., Christ University, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Sentiment and Emotion Analysis of Significant Diseases in India and Russia Subject The topic of the resource Diseases; health care; machine learning; NLP; Sentiment Analysis Description An account of the resource Healthcare organizations need this information to understand and treat the patient's concerns. The motivation for this kind of analysis is how patients provide this information while wrapping it in their thoughts and emotions. It is less practicable to manually study all the free and abundant health-related knowledge accessible online to arrive at decisions that might contribute to an immediate and beneficial decision. Sentiment analysis methods perform this function through automated procedures with minimal human intervention. In this paper, an investigation is conducted to compare the region-wise, language-wise, and sentiment analysis of the tweets collected from Russia and India. The results obtained through research have shown some significant characteristics of the language models used for language detection. The inferenc and analysis obtained from the observations are included in this paper. 2023 IEEE. Creator An entity primarily responsible for making the resource Goswami M.; Bandi U.S. Source A related resource from which the described resource is derived Proceedings of IEEE InC4 2023 - 2023 IEEE International Conference on Contemporary Computing and Communications Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/InC457730.2023.10263114" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/InC457730.2023.10263114</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174719166&doi=10.1109%2FInC457730.2023.10263114&partnerID=40&md5=4d910776291f5535927c99514fd7f342" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174719166&doi=10.1109%2fInC457730.2023.10263114&partnerID=40&md5=4d910776291f5535927c99514fd7f342</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835033577-4 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Goswami M., CHRIST (Deemed to Be University), Department of Computer Science and Engineering, Bangalore, India; Bandi U.S., CHRIST (Deemed to Be University), Department of Computer Science and Engineering, Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Sentimental analysis on Amazon book reviews: A deep learning approach Description An account of the resource [No abstract available] Creator An entity primarily responsible for making the resource Vijayalakshmi A.; Sinha K.; Bose D. Source A related resource from which the described resource is derived Intelligent Systems and Sustainable Computational Models: Concepts, Architecture, and Practical Applications, pp. 188-201. Publisher An entity responsible for making the resource available CRC Press Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1201/9781003407959-12" target="_blank" rel="noreferrer noopener">https://doi.org/10.1201/9781003407959-12</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192850127&doi=10.1201%2F9781003407959-12&partnerID=40&md5=c355521edb12b45731568a9ce16bc0b8" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192850127&doi=10.1201%2f9781003407959-12&partnerID=40&md5=c355521edb12b45731568a9ce16bc0b8</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-104002694-6; 978-103252703-1 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Vijayalakshmi A., Department of Statistics and Data Science, CHRIST (Deemed to be University), Bangalore, India; Sinha K., Department of Statistics and Data Science, CHRIST (Deemed to be University), Bangalore, India; Bose D., Department of Statistics and Data Science, CHRIST (Deemed to be University), Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Sentimental Analysis on Online Education Using Machine Learning Models Subject The topic of the resource Emotion classification; Machine learning; Natural language processing (NLP); Online education; Sentimental analysis Description An account of the resource Sentimental analysis is a simple natural language processing technique for classifying and identifying the sentiments and views represented in a source text. Corona pandemic has shifted the focus of education from traditional classrooms to online classes. Students mental and psychological states alter as a result of this transition. Sentimental study of the opinions of online education students can aid in understanding the students learning conditions. During the corona pandemic, only, students enrolled in online classes were surveyed. Only, students who are in college for pre-graduation, graduation, or post-graduation were used in this study. To grasp the pupils feelings, machine learning models were developed. Using the dataset, we were able to identify and visualize the students feelings. Students favorable, negative, and neutral opinions can be successfully classified using machine learning algorithms. The Naive Bayes method is the most accurate method identified. Logistic regression, support vector machine, decision tree, and random forest these algorithms also gave comparatively good accuracy. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Mathew S.T.; Jacob L. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-462, pp. 413-422. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-19-2211-4_37" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2211-4_37</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135006728&doi=10.1007%2F978-981-19-2211-4_37&partnerID=40&md5=2f8696eb7937a2c2085fcbbc9a3aea22" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135006728&doi=10.1007%2f978-981-19-2211-4_37&partnerID=40&md5=2f8696eb7937a2c2085fcbbc9a3aea22</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981192210-7 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mathew S.T., Department of Data Science, Christ University, Bengaluru, India; Jacob L., Department of Data Science, Christ University, Bengaluru, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Sentimental analysis on voice using AWS comprehend Subject The topic of the resource Aws Athena; Aws Comprehend; Aws Glue; Lambda; NLP; Quick sight; S3; Sentimental analysis; Transcribe Description An account of the resource Sentimental analysis plays an important role in these days because many start-ups have started with user-driven content [1]. Sentiment analysis is an important research area in natural language processing. Natural language processing has a wide range of applications like voice recognition, machine translation, product review, aspect-oriented product analysis, sentiment analysis and text classification etc [2]. This process will improve the business by analyse the emotions of the conversation. In this project author going to perform sentimental analysis using Amazon Comprehend. Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to extract the content of the document. By using this service can extract the unstructured data like images, voice etc. Thus, will identify the emotions of the conversation and give the output whether the conversation is Positive, Negative, Neutral, or Mixed. To perform this author going to use some services from Aws like s3 which is used for the data store, Transcribe which is used for converting the audio to text, Aws Glue is used to generate the metadata from the comprehend file, Aws Comprehend is used to generate the sentiment file from the audio, Lambda is used to trigger from the data store s3, Aws Athena is used to convert text into structured data and finally there is quick sight where he can visualize the data from the given file. 2020 IEEE. Creator An entity primarily responsible for making the resource Satyanarayana G.; Bhuvana J.; Balamurugan M. Source A related resource from which the described resource is derived 2020 International Conference on Computer Communication and Informatics, ICCCI 2020 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2020-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICCCI48352.2020.9104105" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICCCI48352.2020.9104105</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087063912&doi=10.1109%2FICCCI48352.2020.9104105&partnerID=40&md5=af6413e9208aa4532cd692fbb37b1b8a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087063912&doi=10.1109%2fICCCI48352.2020.9104105&partnerID=40&md5=af6413e9208aa4532cd692fbb37b1b8a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-172814513-6 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Satyanarayana G., Jain University, Department of MCA (SCT), Bangalore, India; Bhuvana J., Jain University, Department of MCA, Bangalore, India; Balamurugan M., Christ University, Department of CSE, Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Serendipitous detection of an intense X-ray flare in the weak-line T Tauri star KM Ori with SRG/eROSITA Subject The topic of the resource stars: activity; stars: flare; stars: individual (KM Ori); stars: pre-main sequence; stars: variables: T Tauri; X-rays: stars Description An account of the resource Weak-line T Tauri stars (WTTS) exhibit X-ray flares, likely resulting from magnetic reconnection that heats the stellar plasma to very high temperatures. These flares are difficult to identify through targeted observations. Here, we report the serendipitous detection of the brightest X-ray flaring state of the WTTS KM Ori in the eROSITA DR1 survey. Observations from SRG/eROSITA, Chandra X-ray Observatory, and XMM-Newton are analysed to assess the X-ray properties of KM Ori, thereby establishing its flaring state at the eROSITA epoch. The long-term (1999-2020) X-ray light curve generated for the Chandra observations confirmed that eROSITA captured the source at its highest X-ray flaring state recorded to date. Multi-instrument observations support the X-ray flaring state of the source, with time-averaged X-ray luminosity reaching at the eROSITA epoch, marking it the brightest and possibly the longest flare observed so far. Such intense X-ray flares have been detected only in a few WTTS. The X-ray spectral analysis unveils the presence of multiple thermal plasma components at all epochs. The notably high luminosity , energy (erg), and the elevated emission measures of the thermal components in the eROSITA epoch indicate a superflare/megaflare state of KM Ori. Additionally, the H line equivalent width of from our optical spectral analysis, combined with the lack of infrared excess in the spectral energy distribution, were used to re-confirm the WTTS (thin disc/disc-less) classification of the source. The long-duration flare of KM Ori observed by eROSITA indicates the possibility of a slow-rise top-flat flare. The detection demonstrates the potential of eROSITA to uncover such rare, transient events, thereby providing new insights into the X-ray activity of WTTS. The Author(s), 2025. Published by Cambridge University Press on behalf of Astronomical Society of Australia. Creator An entity primarily responsible for making the resource Ezhikode S.H.; Anilkumar H.; Arun R.; Mathew B.; Jithesh V.; Bhattacharyya S.; Nedhath S.; Cysil T.B.; Muneer S.; Kartha S.S.; Kumar S.P. Source A related resource from which the described resource is derived Publications of the Astronomical Society of Australia, Vol-42 Publisher An entity responsible for making the resource available Cambridge University Press Date A point or period of time associated with an event in the lifecycle of the resource 2025-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1017/pasa.2024.98" target="_blank" rel="noreferrer noopener">https://doi.org/10.1017/pasa.2024.98</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215675608&doi=10.1017%2Fpasa.2024.98&partnerID=40&md5=a826f08b1a166d28ce15e66ff3ee400f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215675608&doi=10.1017%2fpasa.2024.98&partnerID=40&md5=a826f08b1a166d28ce15e66ff3ee400f</a> Rights Information about rights held in and over the resource All Open Access; Green Open Access Relation A related resource ISSN: 13233580 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Ezhikode S.H., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bangalore, India, St. Francis de Sales College (Autonomous), Electronics City, Bengaluru, India; Anilkumar H., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bangalore, India; Arun R., Indian Institute of Astrophysics, Koramangala, Bangalore, India; Mathew B., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bangalore, India; Jithesh V., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bangalore, India; Bhattacharyya S., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bangalore, India, European Organisation for Astronomical Research in the Southern Hemisphere (ESO), Casilla 19001, Santiago, Chile; Nedhath S., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bangalore, India, Indian Institute of Astrophysics, Koramangala, Bangalore, India; Cysil T.B., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bangalore, India; Muneer S., Indian Institute of Astrophysics, Koramangala, Bangalore, India; Kartha S.S., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bangalore, India; Kumar S.P., Indian Institute of Astrophysics, Koramangala, Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Editorials Editorial Faculty Publications- Editorial Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Series Preface Description An account of the resource [No abstract available] Creator An entity primarily responsible for making the resource Bhattacharyya S. Source A related resource from which the described resource is derived Intelligent Multi-modal Data Processing, pp. xix-xx. Publisher An entity responsible for making the resource available wiley Date A point or period of time associated with an event in the lifecycle of the resource 2021-01-01 Identifier An unambiguous reference to the resource within a given context <a href="" target="_blank" rel="noreferrer noopener"></a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152854233&partnerID=40&md5=41ad2e9398b29cfedaa63ef531de193d" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152854233&partnerID=40&md5=41ad2e9398b29cfedaa63ef531de193d</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 2020022620; 978-111957145-2; 2020022619; 978-111957138-4 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Editorial Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Bhattacharyya S., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Series solutions for an unsteady flow and heat transfer of a rotating dusty fluid with radiation effect Subject The topic of the resource Free convection flow; Hall current; Magnetohydrodynamics; Radiation parameter; Rotating dusty fluid; Series solutions Description An account of the resource A theoretical analysis of free convective MHD flow of an unsteady rotating dusty fluid under the influence of hall current and radiation effect is carried out. The fluid flow is considered in the porous media under the influence of periodic pressure gradient and the fluid is assumed to be viscous, incompressible and electrically conducting with uniform distribution of dust particles. The governing partial differential equations are solved analytically using perturbation technique and the expressions for skin-friction is also derived. Further the effect of various pertinent parameter like magnetic parameter, rotation parameter and Hall current parameter on velocity of both fluid and dust phases are depicted graphically and the effect of radiation parameter, Grashof number and Prandtl number on temperature profile is also discussed in detail. 2017, Univerzita Komenskeho. All rights reserved. Creator An entity primarily responsible for making the resource Manjunatha S.; Gireesha B.J.; Bagewadi C.S. Source A related resource from which the described resource is derived Acta Mathematica Universitatis Comenianae, Vol-86, No. 1, pp. 111-125. Publisher An entity responsible for making the resource available Univerzita Komenskeho Date A point or period of time associated with an event in the lifecycle of the resource 2017-01-01 Identifier An unambiguous reference to the resource within a given context <a href="" target="_blank" rel="noreferrer noopener"></a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85009450650&partnerID=40&md5=21d79e02936e8bb74b20c159a57507fd" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85009450650&partnerID=40&md5=21d79e02936e8bb74b20c159a57507fd</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 8629544 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Manjunatha S., Department of Engineering Mathematics, Christ University Faculty of Engineering Kumbalagodu, Mysore Road, Bangalore, 560074, Karnataka-State, India; Gireesha B.J., Department of Studies and Research in Mathematics, Kuvempu University, Shankaraghatta, Shimoga, 577 451, Karnataka, India; Bagewadi C.S., Department of Studies and Research in Mathematics, Kuvempu University, Shankaraghatta, Shimoga, 577 451, Karnataka, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Servant leadership and diversity: A focus on ethnic and cultural diversity Description An account of the resource Business organizations becoming global is nothing new in the current world due to the ever-shrinking physical and communication boundaries. Going global has its benefits and limitations. Benefits would be less expensive land, labor, and resources and reduced transportation cost by being present in countries with vast requirements for an organization's products or services. At the same time, the limitations would be to manage people or lead them toward shared organizational goals. India being a country with enormous opportunities has diverse cultures and practices. Thus, leading various people as employees would be a challenge. What may work in the Western countries may not work in India due to its vast diversity in culture, language, and ethnicity. This research aims to understand the servant leadership approach and if it would be applicable in India. In the context of diverse cultures, the authors analyze the servant leader's role in an organization and compare the practices of servant leadership in various other countries. 2023 by IGI Global. All rights reserved. Creator An entity primarily responsible for making the resource Jaiwant S.V.; Gowda K.R.; Kureethara J.V. Source A related resource from which the described resource is derived Cases on Servant Leadership and Equity, pp. 177-191. Publisher An entity responsible for making the resource available IGI Global Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/978-1-6684-5812-9.ch011" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/978-1-6684-5812-9.ch011</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147628879&doi=10.4018%2F978-1-6684-5812-9.ch011&partnerID=40&md5=7dcce61801077d3eb9e0aae6dfe588ac" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147628879&doi=10.4018%2f978-1-6684-5812-9.ch011&partnerID=40&md5=7dcce61801077d3eb9e0aae6dfe588ac</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166845814-3; 978-166845812-9 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Jaiwant S.V., Christ University, India; Gowda K.R., Christ University, India; Kureethara J.V., Christ University, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Serverless Architecture - A Revolution in Cloud Computing Subject The topic of the resource AWS Lambda; cloud computing; FaaS; Google Cloud Function; Microsoft Azure Function; serverless computing Description An account of the resource Emergence of cloud computing as the inevitable IT computing paradigm, the perception of the compute reference model and building of services has evolved into new dimensions. Serverless computing is an execution model in which the cloud service provider dynamically manages the allocation of compute resources of the server. The consumer is billed for the actual volume of resources consumed by them, instead paying for the pre-purchased units of compute capacity. This model evolved as a way to achieve optimum cost, minimum configuration overheads, and increases the application's ability to scale in the cloud. The prospective of the serverless compute model is well conceived by the major cloud service providers and reflected in the adoption of serverless computing paradigm. This review paper presents a comprehensive study on serverless computing architecture and also extends an experimentation of the working principle of serverless computing reference model adapted by AWS Lambda. The various research avenues in serverless computing are identified and presented. 2018 IEEE. Creator An entity primarily responsible for making the resource Rajan R.A.P. Source A related resource from which the described resource is derived 2018 10th International Conference on Advanced Computing, ICoAC 2018, pp. 88-93. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2018-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICoAC44903.2018.8939081" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICoAC44903.2018.8939081</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078054279&doi=10.1109%2FICoAC44903.2018.8939081&partnerID=40&md5=7e6381767ce717d8b72772abc25f8380" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078054279&doi=10.1109%2fICoAC44903.2018.8939081&partnerID=40&md5=7e6381767ce717d8b72772abc25f8380</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-172810352-5 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Rajan R.A.P., CHRIST (Deemed to Be University), Department of Computer Science, Bengaluru, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Serverless Data Processing System and its Design Space Consideration Subject The topic of the resource Design Space Exploration; Performance Characterization; Sched-Probe Framework; Scheduling Mechanisms; Serverless Data Processing Description An account of the resource Serverless computing is becoming increasingly important in data-processing applications in science and business. The scheduler is at the centre of serverless data-processing systems, allowing for dynamic decisions on job and data placement. The complex design space, which is influenced by various user, cluster, and workload variables, presents problems for developing high-performance and cost-effective scheduling structures and processes. To make this exploration easier, we present Sched-Probe, a framework that includes a conceptual model and simulator for systematic design space exploration. Using the Sched-Probe framework, we evaluate the performance of three scheduling systems and two techniques using real-world workloads. Our open-source software is now available on ExDe, allowing system designers to collaborate on delving into the complexity of serverless scheduling, paving the way for optimised and efficient data-processing systems. 2024, Iquz Galaxy Publisher. All rights reserved. Creator An entity primarily responsible for making the resource Arockia Raj A.; Banerjee K.; Anist A.; Beena Bethel G.N.; Muthu Pandian P.; Acharjee P.B. Source A related resource from which the described resource is derived International Research Journal of Multidisciplinary Scope, Vol-5, No. 4, pp. 641-650. Publisher An entity responsible for making the resource available Iquz Galaxy Publisher Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.47857/irjms.2024.v05i04.01194" target="_blank" rel="noreferrer noopener">https://doi.org/10.47857/irjms.2024.v05i04.01194</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210450137&doi=10.47857%2Firjms.2024.v05i04.01194&partnerID=40&md5=afd0d4494e30a6e92a083c42e7162dca" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210450137&doi=10.47857%2firjms.2024.v05i04.01194&partnerID=40&md5=afd0d4494e30a6e92a083c42e7162dca</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 2582631X Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Arockia Raj A., Department of CSE-Data Science, Madanapalle Institute of Technology and Science, Andhra Pradesh, Madanapalle, India; Banerjee K., Department of CSE, JSS Academy of Technical Education, Noida, India; Anist A., Department of ECE, St.Joseph's Institute of Technology, OMR, Tamilnadu, Chennai, India; Beena Bethel G.N., Department of CSE (Data Science), Sridevi Women's Engineering College, Hyderabad, India; Muthu Pandian P., Department of Chemistry, Saveetha Engineering College, Thandalam, Chennai, India; Acharjee P.B., CHRIST University, Pune Lavasa Campus, Maharashtra, India